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optimize phi3 memory usage again (#11848)

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Yishuo Wang 2024-08-19 17:26:59 +08:00 committed by GitHub
parent 3cd4e87168
commit 9490781aec
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1 changed files with 4 additions and 4 deletions
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python/llm/src/ipex_llm/transformers/models/phi3.py
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@ -177,12 +177,12 @@ def attention_forward(
key_states = repeat_kv(key_states, self.num_key_value_groups) key_states = repeat_kv(key_states, self.num_key_value_groups)
value_states = repeat_kv(value_states, self.num_key_value_groups) value_states = repeat_kv(value_states, self.num_key_value_groups)
attn_weights = torch.matmul(query_states, attn_weights = torch.matmul(query_states, key_states.transpose(2, 3))
key_states.transpose(2, 3)) / math.sqrt(self.head_dim)
# use inplaced div, add and softmax to avoid double attn_weights memory usage
attn_weights.div_(math.sqrt(self.head_dim))
if attention_mask is not None: if attention_mask is not None:
attn_weights = attn_weights + attention_mask attn_weights.add_(attention_mask)
attn_weights = attention_softmax(attn_weights, self.training) attn_weights = attention_softmax(attn_weights, self.training)
attn_weights = torch.nn.functional.dropout(attn_weights, p=self.attention_dropout, attn_weights = torch.nn.functional.dropout(attn_weights, p=self.attention_dropout,